Sensor data correlation and analysis platform

ABSTRACT

Systems and methods for aggregating multiple handheld instruments into a single platform facilitating the collection and transfer of measurement data to a centralized or distributed system. The platform comprises multiple sensor heads made up of the minimum hardware required for application specific sensing with a common interface which communicates with a common interface device that provides power for the sensor, passes data from the sensor modules and transmits it to a computational platform (mobile phone, tablet or computer), and a centrally accessible system to receive data transmitted from the computation platform and stores it.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/547,897, filed Nov. 19, 2014, which claims the benefit of U.S.Provisional Application No. 61/906,985, filed Nov. 21, 2013, U.S.Provisional Application No. 61/907,005, filed Nov. 21, 2013, and U.S.Provisional Application No. 61/906,996, filed Nov. 21, 2013, all ofwhich are incorporated by reference herein in their entireties for allpurposes.

BACKGROUND 1. Field

The present disclosure relates generally to handheld sensors,computation devices and a centralized network. More specifically, thepresent disclosure relates to utilizing an integrated system comprisingone or more modular sensors which utilize a common device to communicatewith a networked computational device such as a mobile phone, tablet orlaptop, and utilizing that networked device to transmit data to acentral server to 1) provide a common platform for the collection sensordata 2) utilize the mobile device to provide processing, present data tothe user, and provide control for the various sensors, and 3) uploaddata from the sensors to a central database.

2. Description of the Related Art

Numerous prior art sensor systems exist for the collection andinterpretation of sensor data. Handheld instruments that collect sensordata and present a representation of the measurement to the user viaon-device screens or limited communication via wired or wirelessnetworking exist. However, all these solutions are stand-alone devicesand not connected to a platform that can aggregate data across one ormore devices and allow the viewing of that data by remote authorizedindividuals. The current devices typical require independent hardware(screens, buttons, processing) for each sensor type and this hardware isredundant across multiple instruments. Each instrument is aself-contained device. This has always presented a problem to users inthe additional size, cost and inconvenience of multiple larger andstand-alone instruments.

Traditionally, users of these stand-alone instruments have had to createtheir own methods of extracting and recording data from the instruments.This typically consists of manually transcribing data from theinstruments on to paper. This process is error prone and doesn't allowan aggregated location for the storage of collected data for analysisand record keeping by businesses. Records are manually cataloged usingpaper storage archival, or copied again in offices to be storeddigitally.

Historically, it has been shown that the existing methods result inseveral deficiencies in these systems including the introduction oferrors during one of the multiple transcription steps. Because ofin-field field dynamics and work constraints, this data transcriptionfrequently occurs after a non-nominal time has elapsed leading toadditional errors being injected into the process. Workers in the fielddon't have access to data when on the job site and there are oftenmultiple people involved during each transcription phase oftenintroducing additional errors.

There is great value in the creation of a common platform for theinstruments, reducing cost of equipment, eliminating the size andinefficiency of the hardware and being able to leverage existingcomputational platforms for the interpretation and presentation ofcollected data to workers in the field. Furthermore, there is asignificant value to the automatic recording of collected data, theautomated integration and layering of that data with additionalcontextual points (e.g. time, location, technician, etc.) andfacilitated transfer of that data to central databases to businessprocesses and accurate recordkeeping.

Field-service based measurements require human interaction to determinewhat measurements are required for inspection and analysis. Somesolutions exist for continuous monitoring of equipment in the field,however it is it is cost prohibitive to outfit every sensor withlong-range connectivity capabilities, and it is necessary to instrumentevery point of a system with instrumentation to effectively monitor allaspects of equipment. This approach results in having to purchase andsupport more sensors than are required to diagnose and maintainfacilities.

Within this industry, field service management systems are focused ontracking people and inventory, determining the dispatch routes andworker locations and inventory levels. With an integrated tool set aspresented herein, these records can be supplemented with equipmentcondition and enable more intelligent decisions around the variousaspects of field service management.

Field service management as described here refers to a hosted orcloud-based system that in combination with hardware and internetservice support companies in managing worker activity, scheduling anddispatching work, and ideally integrating with inventory, billing,accounting and other back-office systems.

It is thus desirable to provide a method and system for a plurality ofusers to interact with a centralized system using a mobile devices andmodular sensor platform to collect data more effectively and transmitsaid data effortlessly and instantly. It is further desirable for thissystem to use on board sensors from the mobile device to provideadditional information about the context of the sensor information, forexample GPS location, time stamp, and user details.

SUMMARY

The present disclosure provides systems and methods for aggregatingmultiple handheld instruments into a single platform facilitating thecollection and transfer of measurement data to a centralized ordistributed system. This platform comprises multiple sensor heads ormodules made up of the minimum hardware required for applicationspecific sensing with a common interface which communicates with acommon interface device that provides power for the sensor, passes datafrom the sensor modules and transmits it to a computational platform(mobile phone, tablet or computer), and a centrally accessible system toreceive data transmitted from the computation platform and stores it.

There are multiple ways to create a system as mentioned, the interfacebetween the sensor modules and the common device could be wired viaseveral connection methods, plugging directly together or connected viacable or wireless means, and using several communications protocols,such as UART, USB, NFC, RF technologies or the like communicationmethods and protocols. The common base could provide some humaninterface to the user. The communication between the common base and thecomputational device could be a wired interface such as cables, a directconnection or a wireless interface such as RF communication, and coulduse any communication protocol supported by the computational device,such as Bluetooth, BLE, 801.11 WiFi, cellular communication or the likeprotocol. The computational device could comprise any processingcomputer such as a laptop, desktop computer, tablet, mobile phone, smartwatch or the like computational device. The communication between thecomputational device and the server could comprise many networkingprotocols to communicate with the central server, including Ethernet,802.11 WiFi, cellular networking, satellite communication or any othermeans of networking. Finally, the central server can comprise manyserver or processing centers, including a remote computer, cloudinfrastructure, remote database, or any other storage and computationalcenter.

A preferred embodiment provides a system and mechanisms to costeffectively deploy and manage a wide array of sensor capabilities thataccomplish the following:

-   -   a) Enable multiple sensors to be used in a common platform to        eliminate redundant hardware and reduce total cost of ownership        of instruments    -   b) Enable users to utilize existing computational hardware for        the processing and human interface of multiple sensors    -   c) Enable users to utilize existing network enabled hardware to        seamlessly transfer manually and automatically gathered sensor        data to a centralized system;    -   d) Enable users with registered devices to receive notifications        when they are within a close proximity to a designated work        assignment;    -   e) Enable information gathered to use existing computational        hardware to supplement sensor data with additional contextual        information    -   f) Store data locally on the computational device and review        historical information

Another advantage of the preferred system is that it enables additionalinteractive user experiences such as:

-   -   a) The sharing of data between users in the field via        notifications of new data collected by other users    -   b) Guidance though a measurement or series of measurements        though software running on the computational device    -   c) The collection of contextual data such as time, location and        identity of the user collecting data to enrich the standard data        collected.

Other advantages of the preferred system and method include:

-   -   a) a mounting mechanism and design that enables a user to change        sensor modules without the need for additional tools;    -   b) a means to transfer sensor data without errors at the time of        data collection;    -   c) an intuitive and efficient method for users to transfer        sensor data in an organized and efficient manner to a        centralized storage space;    -   d) a method by which technical users in the field can retrieve        and compare previously recorded sensor data in the field;    -   e) a method for tracking field technician behavior via data        collected in an automated sensor collection network that can be        accessed by authorized users;    -   f) a method that enables the use of user detection through        registered user's master devices to track actions and associate        these actions with a repair and maintenance profile;    -   g) a secure method for the transmittal of data between a        centralized or distributed system network, a plurality of        sensors, and a master device so only authorized users can access        sensor data through a common point of entry;    -   h) a means to augment additional supplementary information to        collected sensor data by including information generated by the        computational device such as time, location and unique        identifier that can be associated with a user;    -   i) a means to correlate and compare data collected with        intelligent equipment models known to the computational device        or central server.

Thus, the embodiments of the present disclosure provide a more effectiveplatform for sensor data collection spanning multiple measurement typesto improve experience for the purposes of diagnostic, preventativemaintenance and repair. In addition, the embodiments provide a moreeconomical method for using multiple sensors in the field and the uploadand aggregation of sensor data to a centrally accessible platform usingthe network connection existing in the computational device.

These and other objects and advantages of the present invention, alongwith features of novelty appurtenant thereto, will appear or becomeapparent in the course of the following descriptive sections.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following drawings, which form a part of the specification andwhich are to be construed in conjunction therewith, and in which likereference numerals have been employed throughout wherever possible toindicate like parts in the various views:

FIG. 1 is a block diagram of the system.

FIG. 2 is an isometric view of an example sensor module.

FIG. 3 is an isometric view of the common base for the central modules.

FIG. 4 shows a flow diagram of an example method operation.

It should be noted that the figures are not necessarily drawn to scaleand that elements of similar structures or functions are generallyrepresented by like reference numerals for illustrative purposesthroughout the figures. It also should be noted that the figures areonly intended to facilitate the description of the various embodimentsdescribed herein. The figures do not necessarily describe every aspectof the teachings disclosed herein and do not limit the scope of theclaims.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

With initial reference directed to FIG. 1 of the appended drawings, asystem 10 comprising a plurality of sensor modules 30 connected via adata connection 12 comprising a common mechanical and electricalinterface to a common hardware base or interface device 20 whichprovides power and interface between a sensor module 30 and acomputational device 40 comprising a computer, laptop, tablet, phone andthe like. The computational device 40 then transmits recorded data,either automatically or via user direction to the central server 50.

FIG. 2 shows an example implementation of a sensor module 30, comprisinga common interface (e.g., USB) 32 between the module 30 and theinterface device 20.

FIG. 3 shows an example implementation of the common interface device20, which communicates with the sensor modules 30 through a commoninterface 22 and communicates to the computational device 40.

FIG. 4 shows a flow diagram of the typical operation.

Step 1: A sensor module 30 is attached to the common base unit 20. Thisconnection between the sensor module 30 and the common base 20 isperformed by the user by physically attaching the two components.

Step 2: The base unit 20 provides power to the sensor unit 30 anddetects the attachment. This power can be provided via the connector orsome other mechanism, such as wireless charging, or other power transfertechnique. The notification of the sensor attachment can be via anydigital, analog, mechanical or other mechanism to convey the informationto the base unit 20 of an attached sensor 30.

Step 3: The base unit 20 sends a message to the computational device 40to inform the software of the attached sensor 30—or—the computationaldevice 40 requests information about the attached sensor 30 from thebase unit 20. The computational unit 40 running a specific applicationcan then either be notified that a sensor 30 is attached to the baseunit 20, or it can request this information from the base unit 20. Thiscommunication is performed through whatever mechanism the base unit 20is communicating with the computational unit 40. In a preferredembodiment this communication occurs via Bluetooth, however BluetoothLow Energy, WiFi or other wireless communication methods, wiredcommunication such as UART, USB, etc. or any other means of digital oranalog communication.

Step 4: The computational unit 40 requests one or more sensor readingsfrom the base unit 20. The request is sent from the computational unit40 to collect data from the sensor module 30, this could be initiated bythe user or triggered automatically by the detection of the attachedsensor module 30.

Step 5: The base unit 20 requests one or more sensor readings from theattached sensor module 30. The request from the computational unit 40 isrelayed by the base unit 20 and the sensor reading is initiated. Thisrequest of the sensor module 30 may be a command to enter dataacquisition mode for some modules or just the base starting to retrievedata sent by the module, in the case where data is automaticallycollected by the sensor module 30 without previous intervention.

Step 6: The sensor module 30 sends one or more sensor readings to thebase unit 20. This may be the actual starting of a sampling sequence andtransmission of the data, or just the transmission of data which waspreviously being collected, as mentioned in step 5. Additionally, thedata provided by the sensor module 30 may be a single sample point, or astream of multiple data points.

Step 7: The base unit sends one or more sensor readings to thecomputational device 40. The data sent from the sensor module 30 to thebase unit 20 is then relayed by the base unit 20 to the computationaldevice 40 via any means, as mentioned in step 3.

Step 8: The base unit 20 provides sensor specific data processing andshows information to the user. This step comprises any processingrequired for the interpretation and understanding of the data receivedin steps 6 and 7. Example processing operations that may be performedare temporal filtering, (ie. low pass filters, high pass filters)spatial filtering, Kalman filtering, bad data interpretations, signalamplification, digital gain correction, or any other data processingoperations known or to be discovered. Additionally, data presentationand user rendering occurs and is presented to the user. This maycomprise displaying numbers which represent measurements (such astemperature, pressure, etc.), showing images (as in the case of thermalimagers like microbolometers, visible light cameras, network analyzers,spectrum analyzers and other sensors), and the like.

Step 9: Readings are saved by the user. The user can optionally save themeasurements displayed in step 6. This saving can comprise recording theraw data (before processing in step 6), the processed data from step 6or the rendered output of the entire process. Additionally, it caninclude additional information as shown in step 8.

Step 10: Optionally the computational unit 40 can save data from otheron-board sensors. These sensors may be the GPS, accelerometer,magnetometer, compass, camera, or other data if the computational device40 is a mobile phone, or camera, Wifi information, or other parametersif the computational device 40 is a computer. Any additional informationavailable to the computational device 40 can be added as additionalinformation to the sensor saved data.

Step 11: Sensor data and added data is saved and uploaded to the centralserver 50. This upload can be performed using any digital or analogcommunication method. Sample embodiments of this upload mechanism may beWiFi, cellular networks, Ethernet, satellite, or other mechanism.

Step 12: Sensor module 30 removed. If either the sensor module 30 isremoved from the base unit 20, or any other mechanism which results in asimilar response (ie. Battery in the base unit is empty, communicationis lost between the base unit 20 and computational device 40). Theapplication readings halt and operations resume from Step 1.

Step 13: Application stopped. If the application on the computationaldevice 40 is halted, operation will resume from Step 3 when theapplication is resumed (in step 12).

Step 14: Application is resumed after step 11.

From the foregoing, it will be seen that the embodiments presentedherein are well adapted to obtain all the ends and objects herein setforth, together with other advantages that are inherent to thestructure.

It will be understood that certain features and subcombinations are ofutility and may be employed without reference to other features andsubcombinations. This is contemplated by and is within the scope of theclaims.

As many possible embodiments may be made of the invention withoutdeparting from the scope thereof, it is to be understood that all matterherein set forth or shown in the accompanying drawings is to beinterpreted as illustrative and not in a limiting sense.

While the invention is susceptible to various modifications, andalternative forms, specific examples thereof have been shown in thedrawings and are herein described in detail. It should be understood,however, that the invention is not to be limited to the particular formsor methods disclosed, but to the contrary, the invention is to cover allmodifications, equivalents and alternatives falling within the spiritand scope of the appended claims.

In the description above, for purposes of explanation only, specificnomenclature is set forth to provide a thorough understanding of thepresent disclosure. However, it will be apparent to one skilled in theart that these specific details are not required to practice theteachings of the present disclosure.

The various features of the representative examples and the dependentclaims may be combined in ways that are not specifically and explicitlyenumerated in order to provide additional useful embodiments of thepresent teachings. It is also expressly noted that all value ranges orindications of groups of entities disclose every possible intermediatevalue or intermediate entity for the purpose of original disclosure, aswell as for the purpose of restricting the claimed subject matter.

It is understood that the embodiments described herein are for thepurpose of elucidation and should not be considered limiting the subjectmatter of the disclosure. Various modifications, uses, substitutions,combinations, improvements, methods of productions without departingfrom the scope or spirit of the present invention would be evident to aperson skilled in the art. For example, the reader is to understand thatthe specific ordering and combination of process actions describedherein is merely illustrative, unless otherwise stated, and theinvention can be performed using different or additional processactions, or a different combination or ordering of process actions. Asanother example, each feature of one embodiment can be mixed and matchedwith other features shown in other embodiments. Features and processesknown to those of ordinary skill may similarly be incorporated asdesired. Additionally and obviously, features may be added or subtractedas desired. Accordingly, the invention is not to be restricted except inlight of the attached claims and their equivalents.

What is claimed:
 1. A sensor data correlation and analysis apparatus,comprising: one or more sensor modules, wherein each sensor modulecollects one or more measurements associated with one or more ofdiagnosis, preventative maintenance, and repair of an item beingmonitored; and a computational device comprising a communicationinterface for communicating with the one or more sensor modules and oneor more remote server devices; wherein the computational device receivesdata comprising the one or more measurements associated with one or moreof diagnosis, preventative maintenance, and repair of the item beingmonitored, wherein the computational device stores the measurements in arepair and maintenance profile associated with the item being monitored;and wherein the computational device communicates the data via thecommunication interface to the one or more remote server devices.
 2. Theapparatus of claim 1, wherein a measurement is one or more of a digitalimage, a temperature measurement, a pressure measurement, a thermalimage, network analyzer data, and spectrum analyzer data.
 3. Theapparatus of claim 1, wherein the one or more server devices areconfigured to transmit a notification to the apparatus when theapparatus is within a close proximity to the item being monitored andhaving a designated work assignment.
 4. The apparatus of claim 1,wherein the computational device comprises one or more on board sensors.5. The apparatus of claim 4, wherein an on board sensor comprises one ormore of a GPS, accelerometer, magnetometer, compass, digital camera, orWifi information.
 6. The apparatus of claim 1, wherein the computationaldevice is configured to process the data using one or more of temporalfiltering, low pass filters, high pass filters, spatial filtering,Kalman filtering, bad data interpretations, signal amplification, anddigital gain correction.
 7. The apparatus of claim 1, wherein the one ormore remote server devices are configured to process the data using oneor more of temporal filtering, low pass filters, high pass filters,spatial filtering, Kalman filtering, bad data interpretations, signalamplification, and digital gain correction.
 8. The apparatus of claim 1,wherein both the computational device and the one or more remote serverdevices are configured to process the data using one or more of temporalfiltering, low pass filters, high pass filters, spatial filtering,Kalman filtering, bad data interpretations, signal amplification, anddigital gain correction.
 9. A method, comprising: coupling a sensor ofan apparatus to a computational unit of the apparatus, the computationalunit configured to couple to individual ones of a plurality of sensormodules, wherein each sensor module collects a sensor reading in theform of one or more measurements associated with one or more ofdiagnosis, preventative maintenance, and repair of an item beingmonitored, the computational device comprising a communication interfacefor communicating with the plurality of sensor modules and one or moreremote server devices; transmitting one or more sensor readings from thesensor module to the computational unit, wherein the sensor readingscomprising measurements associated with one or more of diagnosis,preventative maintenance, and repair of the item being monitored arestored in a repair and maintenance profile associated with the itembeing monitored; and wherein the computational device receives anotification from the one or more remote server devices when thecomputational device is within a close proximity to the item beingmonitored and having a designated work assignment.
 10. The method ofclaim 9, wherein a measurement is one or more of a digital image, atemperature measurement, a pressure measurement, a thermal image,network analyzer data, and spectrum analyzer data.
 11. The method ofclaim 9, wherein the computational device comprises one or more on boardsensors.
 12. The method of claim 11, wherein an on board sensorcomprises one or more of a GPS, accelerometer, magnetometer, compass,digital camera, or Wifi information.
 13. The method of claim 9, furthercomprising processing the data, by the computational device, using oneor more of temporal filtering, low pass filters, high pass filters,spatial filtering, Kalman filtering, bad data interpretations, signalamplification, and digital gain correction.
 14. The method of claim 9,further comprising processing the data, by the one or more remote serverdevices, using one or more of temporal filtering, low pass filters, highpass filters, spatial filtering, Kalman filtering, bad datainterpretations, signal amplification, and digital gain correction. 15.The method of claim 9, further comprising processing the data, by thecomputational device and the one or more remote server devices, usingone or more of temporal filtering, low pass filters, high pass filters,spatial filtering, Kalman filtering, bad data interpretations, signalamplification, and digital gain correction.
 16. The method of claim 9,further comprising storing, by the computational device, themeasurements in a repair and maintenance profile associated with theitem being monitored.